Clustering protein environments for function prediction: finding PROSITE motifs in 3D

Background: Structural genomics initiatives are producing increasing numbers of three-dimensional (3D) structures for which there is little functional information. Structure-based annotation of molecular function is therefore becoming critical. We previously presented FEATURE, a method for describing microenvironments around functional sites in proteins. However, FEATURE uses supervised machine learning and so is limited to building models for sites of known importance and location. We hypothesized that there are a large number of sites in proteins that are associated with function that have not yet been recognized. Toward that end, we have developed a method for clustering protein microenvironments in order to evaluate the potential for discovering novel sites that have not been previously identified. Results: We have prototyped a computational method for rapid clustering of millions of microenvironments in order to discover residues whose surrounding environments are similar and which may therefore share a functional or structural role. We clustered nearly 2,000,000 environments from 9,600 protein chains and defined 4,550 clusters. As a preliminary validation, we asked whether known 3D environments associated with PROSITE motifs were "rediscovered". We found examples of clusters highly enriched for residues that share PROSITE sequence motifs. Conclusion: Our results demonstrate that we can cluster protein environments successfully using a simplified representation and K-means clustering algorithm. The rediscovery of known 3D motifs allows us to calibrate the size and intercluster distances that characterize useful clusters. This information will then allow us to find new clusters with similar characteristics that represent novel structural or functional sites

Ancient Lowland Maya neighborhoods: Average Nearest Neighbor analysis and kernel density models, environments, and urban scale

Many humans live in large, complex political centers, composed of multi-scalar communities including neighborhoods and districts. Both today and in the past, neighborhoods form a fundamental part of cities and are defined by their spatial, architectural, and material elements. Neighborhoods existed in ancient centers of various scales, and multiple methods have been employed to identify ancient neighborhoods in archaeological contexts. However, the use of different methods for neighborhood identification within the same spatiotemporal setting results in challenges for comparisons within and between ancient societies. Here, we focus on using a single method—combining Average Nearest Neighbor (ANN) and Kernel Density (KD) analyses of household groups—to identify potential neighborhoods based on clusters of households at 23 ancient centers across the Maya Lowlands. While a one-size-fits all model does not work for neighborhood identification everywhere, the ANN/KD method provides quantifiable data on the clustering of ancient households, which can be linked to environmental zones and urban scale. We found that centers in river valleys exhibited greater household clustering compared to centers in upland and escarpment environments. Settlement patterns on flat plains were more dispersed, with little discrete spatial clustering of households. Furthermore, we categorized the ancient Maya centers into discrete urban scales, finding that larger centers had greater variation in household spacing compared to medium-sized and smaller centers. Many larger political centers possess heterogeneity in household clustering between their civic-ceremonial cores, immediate hinterlands, and far peripheries. Smaller centers exhibit greater household clustering compared to larger ones. This paper quantitatively assesses household clustering among nearly two dozen centers across the Maya Lowlands, linking environment and urban scale to settlement patterns. The findings are applicable to ancient societies and modern cities alike; understanding how humans form multi-scalar social groupings, such as neighborhoods, is fundamental to human experience and social organization

Reconciliation of essential process parameters for an enhanced predictability of Arctic stratospheric ozone loss and its climate interactions

Significant reductions in stratospheric ozone occur inside the polar vortices each spring when chlorine radicals produced by heterogeneous reactions on cold particle surfaces in winter destroy ozone mainly in two catalytic cycles, the ClO dimer cycle and the ClO/BrO cycle. Chlorofluorocarbons (CFCs), which are responsible for most of the chlorine currently present in the stratosphere, have been banned by the Montreal Protocol and its amendments, and the ozone layer is predicted to recover to 1980 levels within the next few decades. During the same period, however, climate change is expected to alter the temperature, circulation patterns and chemical composition in the stratosphere, and possible geo-engineering ventures to mitigate climate change may lead to additional changes. To realistically predict the response of the ozone layer to such influences requires the correct representation of all relevant processes. The European project RECONCILE has comprehensively addressed remaining questions in the context of polar ozone depletion, with the objective to quantify the rates of some of the most relevant, yet still uncertain physical and chemical processes. To this end RECONCILE used a broad approach of laboratory experiments, two field missions in the Arctic winter 2009/10 employing the high altitude research aircraft M55-Geophysica and an extensive match ozone sonde campaign, as well as microphysical and chemical transport modelling and data assimilation. Some of the main outcomes of RECONCILE are as follows: (1) vortex meteorology: the 2009/10 Arctic winter was unusually cold at stratospheric levels during the six-week period from mid-December 2009 until the end of January 2010, with reduced transport and mixing across the polar vortex edge; polar vortex stability and how it is influenced by dynamic processes in the troposphere has led to unprecedented, synoptic-scale stratospheric regions with temperatures below the frost point; in these regions stratospheric ice clouds have been observed, extending over >106km2 during more than 3 weeks. (2) Particle microphysics: heterogeneous nucleation of nitric acid trihydrate (NAT) particles in the absence of ice has been unambiguously demonstrated; conversely, the synoptic scale ice clouds also appear to nucleate heterogeneously; a variety of possible heterogeneous nuclei has been characterised by chemical analysis of the non-volatile fraction of the background aerosol; substantial formation of solid particles and denitrification via their sedimentation has been observed and model parameterizations have been improved. (3) Chemistry: strong evidence has been found for significant chlorine activation not only on polar stratospheric clouds (PSCs) but also on cold binary aerosol; laboratory experiments and field data on the ClOOCl photolysis rate and other kinetic parameters have been shown to be consistent with an adequate degree of certainty; no evidence has been found that would support the existence of yet unknown chemical mechanisms making a significant contribution to polar ozone loss. (4) Global modelling: results from process studies have been implemented in a prognostic chemistry climate model (CCM); simulations with improved parameterisations of processes relevant for polar ozone depletion are evaluated against satellite data and other long term records using data assimilation and detrended fluctuation analysis. Finally, measurements and process studies within RECONCILE were also applied to the winter 2010/11, when special meteorological conditions led to the highest chemical ozone loss ever observed in the Arctic. In addition to quantifying the 2010/11 ozone loss and to understand its causes including possible connections to climate change, its impacts were addressed, such as changes in surface ultraviolet (UV) radiation in the densely populated northern mid-latitudes

Reconciliation of essential process parameters for an enhanced predictability of Arctic stratospheric ozone loss and its climate interactions : (RECONCILE) ; activities and results

The international research project RECONCILE has addressed central questions regarding polar ozone depletion, with the objective to quantify some of the most relevant yet still uncertain physical and chemical processes and thereby improve prognostic modelling capabilities to realistically predict the response of the ozone layer to climate change. This overview paper outlines the scope and the general approach of RECONCILE, and it provides a summary of observations and modelling in 2010 and 2011 that have generated an in many respects unprecedented dataset to study processes in the Arctic winter stratosphere. Principally, it summarises important outcomes of RECONCILE including (i) better constraints and enhanced consistency on the set of parameters governing catalytic ozone destruction cycles, (ii) a better understanding of the role of cold binary aerosols in heterogeneous chlorine activation, (iii) an improved scheme of polar stratospheric cloud (PSC) processes that includes heterogeneous nucleation of nitric acid trihydrate (NAT) and ice on non-volatile background aerosol leading to better model parameterisations with respect to denitrification, and (iv) long transient simulations with a chemistry-climate model (CCM) updated based on the results of RECONCILE that better reproduce past ozone trends in Antarctica and are deemed to produce more reliable predictions of future ozone trends. The process studies and the global simulations conducted in RECONCILE show that in the Arctic, ozone depletion uncertainties in the chemical and microphysical processes are now clearly smaller than the sensitivity to dynamic variability

Overfishing Drives Over One-Third of All Sharks and Rays Toward a Global Extinction Crisis

The scale and drivers of marine biodiversity loss are being revealed by the International Union for Conservation of Nature (IUCN) Red List assessment process. We present the first global reassessment of 1,199 species in Class Chondrichthyes-sharks, rays, and chimeras. The first global assessment (in 2014) concluded that one-quarter (24%) of species were threatened. Now, 391 (32.6%) species are threatened with extinction. When this percentage of threat is applied to Data Deficient species, more than one-third (37.5%) of chondrichthyans are estimated to be threatened, with much of this change resulting from new information. Three species are Critically Endangered (Possibly Extinct), representing possibly the first global marine fish extinctions due to overfishing. Consequently, the chondrichthyan extinction rate is potentially 25 extinctions per million species years, comparable to that of terrestrial vertebrates. Overfishing is the universal threat affecting all 391 threatened species and is the sole threat for 67.3% of species and interacts with three other threats for the remaining third: loss and degradation of habitat (31.2% of threatened species), climate change (10.2%), and pollution (6.9%). Species are disproportionately threatened in tropical and subtropical coastal waters. Science-based limits on fishing, effective marine protected areas, and approaches that reduce or eliminate fishing mortality are urgently needed to minimize mortality of threatened species and ensure sustainable catch and trade of others. Immediate action is essential to prevent further extinctions and protect the potential for food security and ecosystem functions provided by this iconic lineage of predators

Accurate Whole-Genome Sequencing and Haplotyping from 10 to 20 Human Cells

Recent advances in whole genome sequencing have brought the vision of personal genomics and genomic medicine closer to reality. However, current methods lack clinical accuracy and the ability to describe the context (haplotypes) in which genome variants co-occur in a cost-effective manner. Here we describe a low-cost DNA sequencing and haplotyping process, Long Fragment Read (LFR) technology, similar to sequencing long single DNA molecules without cloning or separation of metaphase chromosomes. In this study, ten LFR libraries were made using only ~100 pg of human DNA per sample. Up to 97% of the heterozygous single nucleotide variants (SNVs) were assembled into long haplotype contigs. Removal of false positive SNVs not phased by multiple LFR haplotypes resulted in a final genome error rate of 1 in 10 Mb. Cost-effective and accurate genome sequencing and haplotyping from 10-20 human cells, as demonstrated here, will enable comprehensive genetic studies and diverse clinical applications

Degradation of GSPT1 causes TP53-independent cell death in leukemia whilst sparing normal hematopoietic stem cells

Targeted protein degradation is a rapidly advancing and expanding therapeutic approach. Drugs that degrade GSPT1 via the CRL4CRBN ubiquitin ligase are a new class of cancer therapy in active clinical development with evidence of activity against acute myeloid leukemia in early phase trials. However, other than activation of the integrated stress response, the downstream effects of GSPT1 degradation leading to cell death are largely undefined, and no murine models are available to study these agents. We identified the domains of GSPT1 essential for cell survival and show that GSPT1 degradation leads to impaired translation termination, activation of the integrated stress response pathway, and TP53-independent cell death. CRISPR-Cas9 screens implicated decreased translation initiation as protective to GSPT1 degradation, suggesting that cells with higher levels of translation are more susceptible to GSPT1 degradation. We defined two Crbn amino acids that prevent Gspt1 degradation in mice, generated a knock-in mouse with alteration of these residues, and demonstrated the efficacy of GSPT1-degrading drugs in vivo with relative sparing of numbers and function of long-term hematopoietic stem cells. Our results provide a mechanistic basis for the use of GSPT1 degraders for the treatment of cancer, including TP53-mutant AML

Energy determinants GAPDH and NDPK act as genetic modifiers for hepatocyte inclusion formation

Differential expression and activity of the cellular energy regulators GAPDH and NDPK underlie reactive oxygen species–induced damage in the mouse liver and may contribute to human liver disease progression

Mitochondrial Uncoupling Protein-2 (UCP2) Mediates Leptin Protection Against MPP+ Toxicity in Neuronal Cells

Mitochondrial dysfunction is involved in the pathogenesis of neurodegenerative diseases, including Parkinson’s disease (PD). Uncoupling proteins (UCPs) delink ATP production from biofuel oxidation in mitochondria to reduce oxidative stress. UCP2 is expressed in brain, and has neuroprotective effects under various toxic insults. We observed induction of UCP2 expression by leptin in neuronal cultures, and hypothesize that leptin may preserve neuronal survival via UCP2. We showed that leptin preserved cell survival in neuronal SH-SY5Y cells against MPP+ toxicity (widely used in experimental Parkinsonian models) by maintaining ATP levels and mitochondrial membrane potential (MMP); these effects were accompanied by increased UCP2 expression. Leptin had no effect in modulating reactive oxygen species levels. Stable knockdown of UCP2 expression reduced ATP levels, and abolished leptin protection against MPP+-induced mitochondrial depolarization, ATP deficiency, and cell death, indicating that UCP2 is critical in mediating these neuroprotective effects of leptin against MPP+ toxicity. Interestingly, UCP2 knockdown increased UCP4 expression, but not of UCP5. Our findings show that leptin preserves cell survival by maintaining MMP and ATP levels mediated through UCP2 in MPP+-induced toxicity

Multiplexed identification, quantification and genotyping of infectious agents using a semiconductor biochip

The emergence of pathogens resistant to existing antimicrobial drugs is a growing worldwide health crisis that threatens a return to the pre-antibiotic era. To decrease the overuse of antibiotics, molecular diagnostics systems are needed that can rapidly identify pathogens in a clinical sample and determine the presence of mutations that confer drug resistance at the point of care. We developed a fully integrated, miniaturized semiconductor biochip and closed-tube detection chemistry that performs multiplex nucleic acid amplification and sequence analysis. The approach had a high dynamic range of quantification of microbial load and was able to perform comprehensive mutation analysis on up to 1,000 sequences or strands simultaneously in <2 h. We detected and quantified multiple DNA and RNA respiratory viruses in clinical samples with complete concordance to a commercially available test. We also identified 54 drug-resistance-associated mutations that were present in six genes of Mycobacterium tuberculosis, all of which were confirmed by next-generation sequencing